Staff Data Engineer

10 Exchange Place, Jersey City

Job Overview:

Nuts.com is a self-funded, profitable, rapidly growing multi-channel DTC specialty food and wellness company with over 550 people on our team. We're changing the landscape of snacking on nuts, dried fruit, chocolate and more! We planted our roots in Newark, New Jersey during the Great Depression, selling premium nuts on Mulberry Street's open-air market. We've come quite a long way since then, taking our multi-generational family business online in 1999. Even after 95 years, we continue to pride ourselves in expertly sourcing the highest quality foods and treating our customers like family.

What's our team like? We're driven, collaborative and entrepreneurial. Energy and passion power our business and we look for candidates who share in that excitement to help us continue to build something special.

The role:

At Nuts.com, we love our customers, and we love data that tells their story.  And while we’re happy to say that we have a lot of both, we need help bringing it together, managing it, and making it useful -- to us and to our customers. This is where you come in: we’re building our business on this foundation of data, and you’ll make sure it’s a stable one.  

As a technical leader of our data engineering team, reporting to our Director of Business Intelligence, you’ll play a pivotal role in defining the foundation crucial for various types of analysis. Your work will encompass heavy cross-channel analysis of media interaction logs, optimizing paid media, distilling purchase data to better understand our customers, and evaluating warehouse and sourcing data to improve operational efficiency. You will help us think of innovative ways to improve our data systems to help the business make decisions and make it even more enjoyable and valuable to shop with us.  

We have thousands of items, data-driven fulfillment centers, a robust order management system, an exhaustive tagging footprint, a growing number of media outlets, and happy, engaged customers... If you’re already imagining all the cool stuff we’ll be able to build with that, then we should talk.

What you’ll do:

• Apply your engineering expertise to solve large-scale business problems. Drive design and architecture discussions and build alignment on complex technical decisions
• Design, implement, validate, and deploy software solutions to enhance our reporting and analytics systems. This includes new features and architectural improvements for our data pipeline and analytics tools, such as Looker, dbt, Databricks, Fivetran, Airbyte, and AWS Redshift
• Provide technical leadership in data architecture and help establish best practices for data modeling, storage, and retrieval
• Collaborate with cross-functional teams to understand data needs and design solutions that meet business requirements
• Drive the adoption of advanced analytics techniques and technologies to unlock insights from large datasets
• Perform design and code reviews to ensure quality and scalability
• Lead the design of data governance policies and procedures. Help establish and enforce data security and privacy protocols to safeguard sensitive information
• Further agile and DevOps practices to ensure efficient and high-quality data engineering processes
• Support on-call assignments and operational management
• Collaborate with business analysts and product owners to assist with measuring experiments to vet hypotheses
• Mentor, lead, and train other members of the data engineering team
• Be the champion for data from a technical perspective across the entire organization

What you'll bring:

• Bachelor's degree required in Computer Science, Software Engineering, or related field
• Master's degree preferred in a related field
• 6+ years of experience in data engineering working with big data systems that can process and transform data at scale
• Deep knowledge of analytics technologies, modeling techniques, data streaming and other ingestion approaches, data warehousing concepts, cloud platforms (AWS preferred), and proven experience with data architecture including data pipelines, dimensional modeling, and dependency management
• Experience developing with data SaaS and BI tooling (Fivetran, Looker, dbt, Databricks, Apache Airflow, etc.)
• Experience automating data integration using APIs
• Proficiency in programming languages such as SQL and Python in an analytics context
• Experience handling operational aspects of large-scale systems focusing on observability, tech debt management, code refactoring, and robust software development and release processes
• Experience articulating technically complex topics in an easy-t